Data Operations Engineer

McKesson; United States; Remote; USD 80,000 - 110,000; Full time

Job summary

A leading company in healthcare supply chain management is seeking a Data Operations Engineer. This role involves managing data operations, collaborating with various teams, and ensuring data quality and integrity. Ideal candidates will have experience with healthcare data and proficiency in SQL and big data technologies.

Qualifications

• 3-5 years experience with healthcare data types.
• Proficiency in database queries and working with data engineering teams.

Responsibilities

• Manage data operations from ingestion to final product delivery.
• Collaborate with stakeholders to resolve data-related technical issues.

Skills

SQL

Data Modeling

Data Quality Checks

Tools

Databricks

Snowflake

BigQuery

Job description

About McKesson Compile

Established in 1833, McKesson is a US Fortune 10 global leader in healthcare supply chain management solutions, retail pharmacy, healthcare technology, community oncology, and specialty care. We partner with life sciences companies, manufacturers, providers, pharmacies, governments, and other healthcare organizations to help provide the right medicines, medical products, and healthcare services to the right patients at the right time, safely and cost-effectively.

Based in Bangalore, India, McKesson Compile’s data is a comprehensive, fully linked system of record for the US Healthcare market, with intelligence on 2M+ healthcare professionals (HCPs) and over 800K facilities. Compile’s data includes high-quality medical and pharmacy claims, complete Medicare claims (100%), along with provider affiliations and customer master data.

At McKesson, we deliver careers with purpose and potential. Our focus on better health starts with creating an inclusive environment with strong values where you can build a fulfilling career. We provide resources and opportunities to grow and excel, contributing to our mission of improving lives.

Data Operations Engineer

Responsibilities and Duties

1. Manage data operations from ingestion to final product delivery, handling RWD, unstructured healthcare data, and other datasets.
2. Coordinate with vendors and work with the Data Engineering team to load data into the data warehouse.
3. Collaborate with stakeholders including Product, Data, and Design teams to resolve data-related technical issues and support their needs.
4. Ensure timely delivery of data, meeting SLAs for internal and external stakeholders.
5. Assess structural modifications, volume and fill rate consistency, and data comprehensiveness.
6. Investigate production issues to identify causes and implement fixes.
7. Work with cross-functional teams to troubleshoot data problems and develop solutions.
8. Evaluate the integrity of data sources and processes, working with project managers and internal teams to resolve issues and improve procedures.
9. Identify and implement process improvements, such as automation and optimization of data delivery.
10. Stay updated on market events affecting data quality for upcoming refreshes.

Qualifications

• 3-5 years of hands-on experience with healthcare data types, including RWD, claims, EHR, unstructured patient data.
• Proficiency in database queries, SQL, and working with data engineering teams.
• Knowledge of data modeling, validation, quality checks, and engineering concepts.
• Experience with big data technologies such as Databricks, DBT, S3, Delta Lake, Deequ, Griffin, Snowflake, BigQuery.
• Familiarity with version control and CI/CD systems.

Data Quality Assurance

Responsibilities and Duties

1. Develop and review QA plans.
2. Validate incoming and outgoing data to meet quality SLAs.
3. Run tests, identify issues, and collaborate on resolutions.
4. Communicate customer-impacting issues proactively.

Qualifications

• 2-3 years of experience with analytical healthcare data.
• Ability to run automated, semi-automated, and manual tests.
• Experience with healthcare data types, including RWD, claims, EHR, unstructured data.
• Proficiency in database queries, SQL, and working with data engineering teams.
• Experience with QA frameworks like Great Expectations.